Incentive-based website architecture

ABSTRACT

The present invention applies gaming theory and well-understood sales processes and techniques to allow the operator of an interactive sales medium to control what is displayed to a user of the medium in a manner that signals their intentions (e.g., looking for a lower price, looking for a particular incentive, etc.) so that the “strategies” being used by the consumer can be identified and exploited to lead the consumer to a desired end choice. In particular, upon identification of the strategies being used by the consumer, incentives (e.g., gradually increasing rewards and/or decreasing “punishments”) are presented to the consumer in such a way that the margins achieved by an eventual sale are slowly decreased with each presentation of the incentives to the consumer. Since the presentation of each incentive increases the likelihood the consumer will make a purchase, margins are maximized for the seller.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates to the management of visitors to a website and,more particularly, to a system and method for increasing the activity ofa website user through the use of an incentive-based websitearchitecture.

2. Description of the Related Art

The recent explosion in the user of the World Wide Web (hereinafter “theweb”) has created numerous opportunities for content providers such asadvertisers and sellers of products and services to display and sell toconsumers. It is becoming apparent, however, that advertising and salestechniques that in the past were practiced by virtually all advertisersand sellers do not necessarily apply to advertising and sales on theweb.

In a typical “bricks and mortar” sales location, a salesperson oftenwill have in mind certain products that they wish to actively “push” toconsumers. Their goal is to sell as many of the products as possible atthe highest margin possible. However, the salesperson may be willing tosacrifice some of the sales margin in order to make a sale and/or inorder to sell multiple units of the product. Thus, the salesperson will“lead” the customer down a “path” that will ideally result in maximumsales units at a maximum price, but which path is replete with numerousbranches that, from the salesperson's point of view, provide graduallyreduced margins or additional incentives for the buyer to make thepurchase. In other words, the salesperson will whittle away at marginsas slowly as possible until reaching the point at which the buyer isconvinced to make the purchase.

This process has been honed by salespersons over the years to an artform, and salespeople are very much aware of which paths are easier tolead a customer down (and which are harder), as well as which pathsresult in higher (or lower) profits. However, the web does not offer thesame ability for a salesperson to interactively monitor the sale andminimize their “loss” on the original sales price. Typically, e-commercewebsites will offer incentives such as free shipping, a discountedprice, additional items free (e.g., two-for-one) and the like as anincentive to make a sale. However, these incentives are offered to eachcustomer randomly from the beginning, i.e., the website does not offerthe incentive the way a fallback position as a live salesperson would,instead offering them uniformly to all, or a particular class of,customers.

Accordingly, it would be desirable to have available to a seller usingan interactive sales medium (e.g., the World Wide Web, call centers,intelligent vending machines, etc.) the ability to identify the mostlikely paths for the interactive sales medium to be followed during thesales process and be able to provide gradually increasing rewards (ordecreasing “punishments”) along these paths, thereby maximizing themargin on sales made in the interactive sales medium.

SUMMARY OF THE INVENTION

The present invention applies gaming theory and well-understood salesprocesses and techniques to allow the operator of an interactive salesmedium to control what is displayed to a user of the medium in a mannerthat signals their intentions (e.g., looking for a lower price, lookingfor a particular incentive, etc.) so that the “strategies” being used bythe consumer can be identified and exploited. In particular, uponidentification of the strategies being used by the consumer, incentives(e.g., gradually increasing rewards and/or decreasing “punishments”) arepresented to the consumer in such a way that the margins achieved by aneventual sale are gradually decreased with each presentation of theincentives to the consumer. Since the presentation of each incentiveincreases the likelihood the consumer will make a purchase, margins aremaximized for the seller.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flowchart illustrating generally steps taken by a websitedeveloper to take advantage of the present invention;

FIG. 2 is a flowchart illustrating the operation of a websiteconstructed using the principles illustrated in FIG. 1; and

FIG. 3 is a tree diagram illustrating the overall concept of the presentinvention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 1 is a flowchart illustrating generally steps taken by a websitedeveloper to take advantage of the present invention. It is understoodthat the present invention is not limited to website sales and hasapplicability to any interactive medium in which a user/consumer isgiven choices and can make selections without intervention by asalesperson.

The term “incentive” as used herein refers to any action whichencourages action by a user of the system, and the stronger an incentiveis, the more likely it is to encourage the desired action. For example,rewards such as free shipping, two-for-one deals, discounts onsubsequent purchases, or time-based rewards (e.g., “order in 60 secondsto receive X”) are contemplated as being “positive incentives”. Further,“negative incentives” can also be used in the form of “punishments” asused in gaming theory parlance. For example, the user could be given a“purchase now and receive free shipping” option, and if they fail tomake the selection, subsequently be given a “purchase now and receive80% off shipping” option, or shipping insurance could be initiallyoffered, and then rescinded if the user declines the initial offer butcontinues to show interest. Thus, the user will see that there isbenefit to selecting early in the process instead of continuing on,since the incentives offer reduced benefits the longer the user waits tomake the purchase.

Referring to FIG. 1, at step 102, all potential selection possibilitiesare identified. In the context of a website, this would involveidentifying each web page, and each link within the site presented to aviewer of a particular web page.

At step 104, initial selection probabilities are assigned to eachpossible content-selection. Since, at this point, there is no dataavailable regarding selection probabilities, these initial (default)selection possibilities are based on estimation.

At step 106, data obtained from actual use of the content deliverysystem is gathered and analyzed. Typically, this would be in the form ofclickstream data for websites. In particular, the paths taken by usersto an end result (e.g., the selection of an item for purchase) areidentified and probabilities established with respect to the likelihoodthat particular selections will eventually lead to subsequent selectionsand the eventual end result.

At step 108, based on the analysis performed in step 106, incentives areestablished to “draw” users to make selections that have a relativelylow probability of being made. In other words, choices that have a highprobability of being selected, that is, that require little or noincentive to select, will either be associated with no incentive or beassociated with an incentive of very low strength.

In contrast, more difficult paths to lure customers down, i.e., thosewith low selection probabilities, are given relatively strongerincentives, since the statistical analysis shows that these paths areless likely to be taken without incentive.

At step 110, modification of the incentives is performed whenever newhistorical data obtained indicates different probabilities than existedpreviously.

Thus, using the steps illustrated in FIG. 1, a website is analyzed toidentify paths least likely to be followed, and incentives are thenassigned to these paths so that they are more likely to be followed.

FIG. 2 is a flowchart illustrating the operation of a websiteconstructed using the principles illustrated in FIG. 1. Referring toFIG. 2, at step 200, a user enters the site, and at step 202, the usermakes an initial selection, e.g., by clicking on a “new products” or“clearance” or other icon displayed on the website. At step 204, theuser is presented with incentives (if appropriate) based upon theprobable sub-selections within the selected category that are available.At step 206, the user makes a selection, and at step 208 a determinationis made as to whether or not there are additional sub-selectionsavailable. If there are, the process proceeds back to step 204, and theuser is presented with additional incentives (if appropriate). If thereare no additional sub-selections available, e.g., if the result is“purchase”, then the process proceeds to a site termination point atstep 210, and the site activity is completed and the user exits at step212.

FIG. 3 is a tree diagram illustrating the overall concept of the presentinvention applied to a simple e-commerce website. A homepage 300 isillustrated with six selections 302, 304, 306, 308, 310, and 312illustrated as being available from homepage 300.

As shown, selection 302 corresponds to “new products”, selection 304corresponds to “accessories”, selection 306 corresponds to “discount”,selection 308 corresponds to “clearance”, selection 310 corresponds to“high margin”, and selection 312 corresponds to “about”. It is notedthat these may not be the specific labels that would appear on thewebsite. For example, high margin items would not typically be listedunder the term “high margin” but would instead have another name, butthe products that are associated with selection 310 are, in thisexample, high margin items.

The example of FIG. 3 follows two alternative paths. The first pathrelates to clearance selection 308 and the second path relates to highmargin selection 310. As shown on the webpage 300, each of thenavigation buttons has a probability associated with it. Theseprobabilities are initially set based on estimation and then are revisedbased on historical analysis of traffic through the website. As can beseen, selection 302 has a one-out-of-six probability, selection 304 hasa 0.5-out-of-six probability, selection 306 has a two-out-of-sixprobability, selection 308 has a two-out-of-six probability, selection310 has a 0.25-out-of-six probability, and selection 312 has a0.25-out-of-six probability.

As illustrated in FIG. 3, the clearance selection has a two-out-of-sixprobability of being selected. Relative to the other choices, this is ahigh probability. Upon selecting selection 308, the user will bepresented with a series of products available for purchase that havebeen characterized as clearance items. As shown in selection 308, thereis a four-out-of-ten probability that the user selecting the clearanceselection will select, for viewing, information regarding selection 314corresponding to “Product 15”. Following the path illustrated in FIG. 3,there is only a one-in-twenty chance that, after selecting Product 15for viewing, the purchaser will proceed to selection 316 and add it totheir “basket”. Since this is a relatively low probability, the user isgiven an incentive to add the item to their basket, in this example,free returns if they do not like the item for any reason. Once the itemhas been added to the basket, there is a two-out-of-ten likelihood thatthey will proceed to choice 318 and check-out, meaning complete andpurchase the item (referred to generally as a “desired end choice”). Soto increase the probability that they will actually proceed to thedesired end choice (check-out and buy the item), free shipping isoffered as an incentive at this point.

The alternative path shown in FIG. 3 is for the selection of high marginproducts by selection of the button 310 associated with high marginproducts. As can be seen in FIG. 3, the probability of somebodyselecting these high margin products from the homepage are small at0.25-out-of-six. Thus, in order to encourage its selection, freeshipping is given as an option immediately. Once selecting the highmargin selection 310, a series of products are illustrated for the userwith choice 320 (Product 1) being among them. The probability of Product1 being selected is two-out-of-ten, so to encourage a user to go furtherand add Product 1 to their basket (choice 322), they are given anincentive of free insurance on the shipping. Once the person has addedthis item to their basket with free shipping and free insurance, theprobability of them proceeding to check-out (choice 324) isnine-out-of-ten. Since it is such a high probability that they willproceed to the desired end choice (go to check-out), there is noincentive offered at this point.

The concept of the present invention is based upon gaming theory. Gamingtheory is the science of how games of chance work. Considering theplayers, the strategic environment, and payoffs, the present inventionproposes applying game theory to managing visitors to a website. Thestrategy is based on interaction with potential and present customers(players). Considering the web server to be one player, and the customerto be another player, fellow players can be rewarded/punished based uponchoices made during operation of the website. Margin is conceded toachieve a sale. The variables to be optimized are the margin vs. thesize of the market basket. Strategies are based on the historical pathstaken through the website, which are tracked, and from thatprobabilities are calculated as to the next potential step. Reward andpunishment (incentives) take the form of discounts or removal of options(free shipping, free package insurance, etc.). Historical web pagehistorical probability weighting is used. The paths are ordered by theprobability of the most gain (basket size and profitability). Using gametheory analysis, the best business outcome for a visit to a site orinteractive channel are identified. An existing website is preanalyzedto establish the “rules” of the “game”. Reward and punishment are usedinteractively.

The above-described steps can be implemented using standard well-knownprogramming techniques. The novelty of the above-described embodimentlies not in the specific programming techniques but in the use of thesteps described to achieve the described results. Software programmingcode which embodies the present invention is typically stored inpermanent storage of some type, such as permanent storage of a webserver offering the interactive experience. In a client/serverenvironment, such software programming code may be stored with storageassociated with a server. The software programming code may be embodiedon any of a variety of known media for use with a data processingsystem, such as a diskette, or hard drive, or CD-ROM. The code may bedistributed on such media, or may be distributed to users from thememory or storage of one computer system over a network of some type toother computer systems for use by users of such other systems. Thetechniques and methods for embodying software program code on physicalmedia and/or distributing software code via networks are well known andwill not be further discussed herein.

It will be understood that each element of the illustrations, andcombinations of elements in the illustrations, can be implemented bygeneral and/or special purpose hardware-based systems that perform thespecified functions or steps, or by combinations of general and/orspecial-purpose hardware and computer instructions.

These program instructions may be provided to a processor to produce amachine, such that the instructions that execute on the processor createmeans for implementing the functions specified in the illustrations. Thecomputer program instructions may be executed by a processor to cause aseries of operational steps to be performed by the processor to producea computer-implemented process such that the instructions that executeon the processor provide steps for implementing the functions specifiedin the illustrations. Accordingly, FIGS. 1-3 support combinations ofmeans for performing the specified functions, combinations of steps forperforming the specified functions, and program instruction means forperforming the specified functions.

While there has been described herein the principles of the invention,it is to be understood by those skilled in the art that this descriptionis made only by way of example and not as a limitation to the scope ofthe invention. Accordingly, it is intended by the appended claims, tocover all modifications of the invention which fall within the truespirit and scope of the invention.

Although the present invention has been described with respect to aspecific preferred embodiment thereof, various changes and modificationsmay be suggested to one skilled in the art and it is intended that thepresent invention encompass such changes and modifications as fallwithin the scope of the appended claims.

1. A method of influencing the actions of users of an interactivecontent-delivery system, comprising the steps of: identifyingprobabilities of selection with respect to selections offered by saidinteractive content-delivery system; and presenting users of saidinteractive content-delivery system with incentives based upon saidanalysis.
 2. The method of claim 1, wherein said identifying stepincludes at least the step of: estimating probabilities of selection foreach possible selection offered by said interactive content deliverysystem if historical user data for said interactive content deliverysystem is unavailable.
 3. The method of claim 2, wherein saididentifying step further comprises at least the step of analyzinghistorical user data for said interactive content delivery system toidentify probability of selection based on said historical user data. 4.The method of claim 3, wherein said step of analyzing historical userdata comprises at least the step of performing historical analysis ofpaths taken by users who have not been presented with incentives.
 5. Themethod of claim 3, wherein said step of analyzing historical user datais continually updated with new historical user data obtained afterusers of said interactive content-delivery system have been presentedwith incentives in accordance with the present invention.
 6. The methodof claim 3, wherein said incentives are selected based on gaming theoryand include both positive and negative incentives.
 7. The method ofclaim 6, wherein said interactive content-delivery system comprises aweb-based e-commerce site.
 8. A method of managing website visitors,comprising the steps of: receiving a content selection from a websiteuser; analyzing said content selection and determining probabilitiesassociated with the selection of a sub-choice presented to said userbased on said content selection; presenting incentives associated witheach sub-choice based upon said probabilities; and repeating the abovesteps until a desired end choice has been selected.
 9. A system forinfluencing the actions of users of an interactive content-deliverysystem, comprising: means for identifying probabilities of selectionwith respect to selections offered by said interactive content-deliverysystem; and means for presenting users of said interactivecontent-delivery system with incentives based upon said analysis. 10.The system of claim 9, wherein said means for identifying includes atleast: means for estimating probabilities of selection for each possibleselection offered by said interactive content delivery system ifhistorical user data for said interactive content delivery system isunavailable.
 11. The system of claim 10, wherein said means foridentifying further comprises at least means for analyzing historicaluser data for said interactive content delivery system to identifyprobability of selection based on said historical user data.
 12. Thesystem of claim 11, wherein said means for analyzing historical userdata comprises at least means for performing historical analysis ofpaths taken by users who have not been presented with incentives. 13.The system of claim 11, wherein said means for analyzing historical userdata is continually updated with new historical user data obtained afterusers of said interactive content-delivery system have been presentedwith incentives in accordance with the present invention.
 14. The systemof claim 11, wherein said incentives are selected based on gaming theoryand include both positive and negative incentives.
 15. The system ofclaim 14, wherein said interactive content-delivery system comprises aweb-based e-commerce site.
 16. A computer program product forinfluencing the actions of users of an interactive content-deliverysystem, comprising a computer-readable storage medium havingcomputer-readable program code embodied in the medium, thecomputer-readable program code comprising: computer-readable programcode that identifies probabilities of selection with respect toselections offered by said interactive content-delivery system; andcomputer-readable program code that presents users of said interactivecontent-delivery system with incentives based upon said analysis. 17.The computer program product of claim 16, wherein said computer-readableprogram code that identifies probabilities of selection includes:computer-readable program code that estimates probabilities of selectionfor each possible selection offered by said interactive content deliverysystem if historical user data for said interactive content deliverysystem is unavailable.
 18. The computer program product of claim 17,wherein said computer-readable program code that identifiesprobabilities of selection further comprises computer-readable programcode that analyzes historical user data for said interactive contentdelivery system to identify probability of selection based on saidhistorical user data.
 19. The computer program product of claim 18,wherein said computer-readable program code that analyzes historicaluser data comprises at least computer-readable program code thatperforms historical analysis of paths taken by users who have not beenpresented with incentives.
 20. The computer program product of claim 18,wherein said computer-readable program code that analyzes historicaluser data is continually updated with new historical user data obtainedafter users of said interactive content-delivery system have beenpresented with incentives in accordance with the present invention. 21.The computer program product of claim 18, wherein said incentives areselected based on gaming theory and include both positive and negativeincentives.
 22. The computer program product of claim 21, wherein saidinteractive content-delivery system comprises a web-based e-commercesite.